In [1]:
from urllib.request import urlopen
import json
with urlopen('https://raw.githubusercontent.com/plotly/datasets/master/geojson-counties-fips.json') as response:
    counties = json.load(response)

counties["features"][0]
Out[1]:
{'type': 'Feature',
 'properties': {'GEO_ID': '0500000US01001',
  'STATE': '01',
  'COUNTY': '001',
  'NAME': 'Autauga',
  'LSAD': 'County',
  'CENSUSAREA': 594.436},
 'geometry': {'type': 'Polygon',
  'coordinates': [[[-86.496774, 32.344437],
    [-86.717897, 32.402814],
    [-86.814912, 32.340803],
    [-86.890581, 32.502974],
    [-86.917595, 32.664169],
    [-86.71339, 32.661732],
    [-86.714219, 32.705694],
    [-86.413116, 32.707386],
    [-86.411172, 32.409937],
    [-86.496774, 32.344437]]]},
 'id': '01001'}
In [2]:
import pandas as pd
df = pd.read_csv("https://raw.githubusercontent.com/plotly/datasets/master/fips-unemp-16.csv",
                   dtype={"fips": str})
df.head()
Out[2]:
fips unemp
0 01001 5.3
1 01003 5.4
2 01005 8.6
3 01007 6.6
4 01009 5.5
In [3]:
from urllib.request import urlopen
import json
with urlopen('https://raw.githubusercontent.com/plotly/datasets/master/geojson-counties-fips.json') as response:
    counties = json.load(response)

import pandas as pd
df = pd.read_csv("https://raw.githubusercontent.com/plotly/datasets/master/fips-unemp-16.csv",
                   dtype={"fips": str})

import plotly.express as px

fig = px.choropleth(df, geojson=counties, locations='fips', color='unemp',
                           color_continuous_scale="Viridis",
                           range_color=(0, 12),
                           scope="usa",
                           labels={'unemp':'unemployment rate'}
                          )
fig.update_layout(margin={"r":0,"t":0,"l":0,"b":0})
fig.show()
In [4]:
import plotly.express as px

df = px.data.election()
geojson = px.data.election_geojson()

fig = px.choropleth(df, geojson=geojson, color="Bergeron",
                    locations="district", featureidkey="properties.district",
                    projection="mercator"
                   )
fig.update_geos(fitbounds="locations", visible=False)
fig.update_layout(margin={"r":0,"t":0,"l":0,"b":0})
fig.show()
In [5]:
import plotly.express as px

df = px.data.election()
geojson = px.data.election_geojson()

fig = px.choropleth(df, geojson=geojson, color="winner",
                    locations="district", featureidkey="properties.district",
                    projection="mercator", hover_data=["Bergeron", "Coderre", "Joly"]
                   )
fig.update_geos(fitbounds="locations", visible=False)
fig.update_layout(margin={"r":0,"t":0,"l":0,"b":0})
fig.show()
In [6]:
import plotly.express as px
import geopandas as gpd

df = px.data.election()
geo_df = gpd.GeoDataFrame.from_features(
    px.data.election_geojson()["features"]
).merge(df, on="district").set_index("district")

fig = px.choropleth(geo_df,
                   geojson=geo_df.geometry,
                   locations=geo_df.index,
                   color="Joly",
                   projection="mercator")
fig.update_geos(fitbounds="locations", visible=False)
fig.show()

---------------------------------------------------------------------------
OSError                                   Traceback (most recent call last)
/var/folders/tt/hzn__v4945bfpj662bgrkr4h0000gn/T/ipykernel_45845/1092348108.py in <module>
      1 import plotly.express as px
----> 2 import geopandas as gpd
      3 
      4 df = px.data.election()
      5 geo_df = gpd.GeoDataFrame.from_features(

/usr/local/anaconda3/envs/plotly/lib/python3.8/site-packages/geopandas/__init__.py in <module>
----> 1 from geopandas.geoseries import GeoSeries  # noqa
      2 from geopandas.geodataframe import GeoDataFrame  # noqa
      3 from geopandas.array import _points_from_xy as points_from_xy  # noqa
      4 
      5 from geopandas.io.file import read_file  # noqa

/usr/local/anaconda3/envs/plotly/lib/python3.8/site-packages/geopandas/geoseries.py in <module>
     10 
     11 import pyproj
---> 12 from shapely.geometry.base import BaseGeometry
     13 from shapely.ops import transform
     14 

/usr/local/anaconda3/envs/plotly/lib/python3.8/site-packages/shapely/geometry/__init__.py in <module>
      2 """
      3 
----> 4 from .base import CAP_STYLE, JOIN_STYLE
      5 from .geo import box, shape, asShape, mapping
      6 from .point import Point, asPoint

/usr/local/anaconda3/envs/plotly/lib/python3.8/site-packages/shapely/geometry/base.py in <module>
     15 
     16 from shapely.affinity import affine_transform
---> 17 from shapely.coords import CoordinateSequence
     18 from shapely.errors import WKBReadingError, WKTReadingError
     19 from shapely.ftools import wraps

/usr/local/anaconda3/envs/plotly/lib/python3.8/site-packages/shapely/coords.py in <module>
      6 from ctypes import byref, c_double, c_uint
      7 
----> 8 from shapely.geos import lgeos
      9 from shapely.topology import Validating
     10 

/usr/local/anaconda3/envs/plotly/lib/python3.8/site-packages/shapely/geos.py in <module>
    111         _lgeos = load_dll('geos_c', fallbacks=alt_paths)
    112 
--> 113     free = load_dll('c').free
    114     free.argtypes = [c_void_p]
    115     free.restype = None

/usr/local/anaconda3/envs/plotly/lib/python3.8/site-packages/shapely/geos.py in load_dll(libname, fallbacks, mode)
     52     else:
     53         # No shared library was loaded. Raise OSError.
---> 54         raise OSError(
     55             "Could not find lib {0} or load any of its variants {1}.".format(
     56                 libname, fallbacks or []))

OSError: Could not find lib c or load any of its variants [].
In [ ]:
import plotly.express as px

df = px.data.gapminder().query("year==2007")
fig = px.choropleth(df, locations="iso_alpha",
                    color="lifeExp", # lifeExp is a column of gapminder
                    hover_name="country", # column to add to hover information
                    color_continuous_scale=px.colors.sequential.Plasma)
fig.show()
In [ ]:
import plotly.express as px

fig = px.choropleth(locations=["CA", "TX", "NY"], locationmode="USA-states", color=[1,2,3], scope="usa")
fig.show()
In [ ]:
import plotly.graph_objects as go

import pandas as pd
df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/2011_us_ag_exports.csv')

fig = go.Figure(data=go.Choropleth(
    locations=df['code'], # Spatial coordinates
    z = df['total exports'].astype(float), # Data to be color-coded
    locationmode = 'USA-states', # set of locations match entries in `locations`
    colorscale = 'Reds',
    colorbar_title = "Millions USD",
))

fig.update_layout(
    title_text = '2011 US Agriculture Exports by State',
    geo_scope='usa', # limite map scope to USA
)

fig.show()
In [ ]:
import plotly.graph_objects as go

import pandas as pd
df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/2011_us_ag_exports.csv')

for col in df.columns:
    df[col] = df[col].astype(str)

df['text'] = df['state'] + '<br>' + \
    'Beef ' + df['beef'] + ' Dairy ' + df['dairy'] + '<br>' + \
    'Fruits ' + df['total fruits'] + ' Veggies ' + df['total veggies'] + '<br>' + \
    'Wheat ' + df['wheat'] + ' Corn ' + df['corn']

fig = go.Figure(data=go.Choropleth(
    locations=df['code'],
    z=df['total exports'].astype(float),
    locationmode='USA-states',
    colorscale='Reds',
    autocolorscale=False,
    text=df['text'], # hover text
    marker_line_color='white', # line markers between states
    colorbar_title="Millions USD"
))

fig.update_layout(
    title_text='2011 US Agriculture Exports by State<br>(Hover for breakdown)',
    geo = dict(
        scope='usa',
        projection=go.layout.geo.Projection(type = 'albers usa'),
        showlakes=True, # lakes
        lakecolor='rgb(255, 255, 255)'),
)

fig.show()
In [ ]:
import plotly.graph_objects as go
import pandas as pd

df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/2014_world_gdp_with_codes.csv')

fig = go.Figure(data=go.Choropleth(
    locations = df['CODE'],
    z = df['GDP (BILLIONS)'],
    text = df['COUNTRY'],
    colorscale = 'Blues',
    autocolorscale=False,
    reversescale=True,
    marker_line_color='darkgray',
    marker_line_width=0.5,
    colorbar_tickprefix = '$',
    colorbar_title = 'GDP<br>Billions US$',
))

fig.update_layout(
    title_text='2014 Global GDP',
    geo=dict(
        showframe=False,
        showcoastlines=False,
        projection_type='equirectangular'
    ),
    annotations = [dict(
        x=0.55,
        y=0.1,
        xref='paper',
        yref='paper',
        text='Source: <a href="https://www.cia.gov/library/publications/the-world-factbook/fields/2195.html">\
            CIA World Factbook</a>',
        showarrow = False
    )]
)

fig.show()
In [ ]:
import plotly.figure_factory as ff

import numpy as np
import pandas as pd

df_sample = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/laucnty16.csv')
df_sample['State FIPS Code'] = df_sample['State FIPS Code'].apply(lambda x: str(x).zfill(2))
df_sample['County FIPS Code'] = df_sample['County FIPS Code'].apply(lambda x: str(x).zfill(3))
df_sample['FIPS'] = df_sample['State FIPS Code'] + df_sample['County FIPS Code']

colorscale = ["#f7fbff", "#ebf3fb", "#deebf7", "#d2e3f3", "#c6dbef", "#b3d2e9", "#9ecae1",
    "#85bcdb", "#6baed6", "#57a0ce", "#4292c6", "#3082be", "#2171b5", "#1361a9",
    "#08519c", "#0b4083", "#08306b"
]
endpts = list(np.linspace(1, 12, len(colorscale) - 1))
fips = df_sample['FIPS'].tolist()
values = df_sample['Unemployment Rate (%)'].tolist()


fig = ff.create_choropleth(
    fips=fips, values=values, scope=['usa'],
    binning_endpoints=endpts, colorscale=colorscale,
    show_state_data=False,
    show_hover=True,
    asp = 2.9,
    title_text = 'USA by Unemployment %',
    legend_title = '% unemployed'
)
fig.layout.template = None
fig.show()
In [ ]: